1. Field of the Invention
The invention relates generally to wireless communication and more particularly to systems and methods for ensuring adequate performance of a wireless communication device within a wireless communication system.
2. Background
Before a wireless communication device leaves the factory for deployment in a wireless communication system, it is tested to ensure it complies with all system performance requirements. Such a device must not only be tested to ensure that it performs when RF propagation conditions are optimal, but also when conditions are poor as well as when multiple RF sources exist. This means that the device must be tested to ensure that it performs even when fading and path loss are present in all possible propagation paths, with delay spread and fading power spectrum, between the device and the multiple RF sources. Further, the device must be tested for both Line of Sight (LOS) signals and non-LOS signals.
Multipath can best be described as the result of reflection, diffraction, and scattering, by bodies, such as buildings 106, mountains 108, etc., of a signal 102 transmitted from a base station transmitter 104 to a device 110 in a communication system 100 as illustrated in FIG. 1. When signal 102 is transmitted, it is broadcast within the communication cell, or sector, defined by the particular base station transmitter 104 and/or base station antenna 104a being used. Thus, signal 102 begins to travel along a propagation path 112 toward device 110. As signal 102 travels along propagation path 112, it will encounter bodies 106 and/or 108. By reflection, diffraction, and scattering, these bodies 106 and 108 will redirect portions of the energy comprising signal 102 along different paths, e.g., propagation paths 114, 116, and 118. Some or all of the signals traveling along these new paths will reach device 110 along with signal 102 traveling along path 112.
For purposes of this specification path 112 is termed the primary path, while paths 114, 116, and 118 are termed multipaths. Similarly, a signal traveling along primary path 112 is termed the specular signal or the LOS signal, while signals traveling along multipaths 114, 116, and 118 are termed multipath signals or simply multipaths. To eliminate any confusion, when the term multipath, or multipaths, is used in this specification and the claims that follow, it will be understood that the actual signal is being referred to, as opposed to the signal path, unless otherwise indicated.
When the multipaths reach device 110, they will combine with specular signal 102 travelling along path 112. In complicated wireless systems, such as a commercial IS-95 compliant cellular communication system, the signal sources of received multipaths could have originated from more than one base station. In a static multipath situation, the multipaths have traveled along different paths and will be delayed and attenuated with respect to the primary path and the original signal intensity, respectively. Thus the delay spread of the multipaths at the receiver causes the received multipath signals to be phase shifted with respect to received specular signal 102 travelling along path 112 as well as with each other.
In a dynamic multipath situation, the receiver, e.g., the receiver in device 110, is moving in propagation field, which causes a time variation of each multipath length. Here, the rate of path change for any particular multipath is related to the velocity of the receiver and the angle between the moving direction and that multipath, which is indirectly related to the Doppler frequency shift.
As a result of both static and dynamic fading, the multipaths will combine destructively and constructively in the receiver of device 110, forming a RF signal with a randomly changing envelope and phase. This prevents, or makes difficult, reception of specular signal 102. The effect described is termed fast fading and is a serious problem in all wireless communication systems. Fast fading of a non-LOS signal, called Rayleigh fading, it more severe in terms of the distributed envelope than fast fading of a LOS signal. The later situation is referred to as Rician Fading. Thus, it is more difficult to detect the already weak non-LOS signals in a wireless communication system.
The multipath interference also causes the fading of received signal components in the frequency domain. This fading, sometimes called Power Spectral Density (PSD) fading, is associated with fast fading and Doppler shift described above. PSD fading must be considered when designing and/or testing devices for use in some wireless communication systems, e.g. in an IS-95 compliant communication system. Some communication systems attempt to separate and filter out the multipaths in the receiver, others attempt to use the energy contained in the multipaths to increase the sensitivity and performance of the receiver, e.g., the Rake receiver adopted in IS-95 complaint system. Regardless of the approach used, however, device 110 must be tested before it leaves the factory to ensure that it will perform even in the presence of multipaths.
There are other factors that contribute to a received signal's fading, attenuation, and delay, which are due to poor radio signal propagation conditions. These factors include mean path loss, i.e., the mean signal attenuation versus distance and slow fading, also called shadow fading or log-normal fading, which is due in part to changing terrain contours. The measured mean path loss can introduce 6˜8 dB variations to the theoretically predicted mean path loss in one signal source case. Further, fast fading can superimpose up to +10˜−30 dB of variation onto the slow fading variations when there is no LOS or specular signal 102 component present.
In addition, the presence of multiple sectors and many base stations with the same or different carry frequencies within the wireless communication system can complicate the operation of a wireless communication device. For example, in an IS-95 compliant system, the receiver in a wireless communication device constantly searches for pilot signals from sectors other than the one with which it is currently communicating. If the strength of one these other pilot signals exceeds the strength of the pilot from the current sector by a predetermined amount, then the device will “handoff” to the new sector. In order to manage handoffs effectively, the device must be able to accurately determine the pilot signal strengths. Otherwise, the device will either make unnecessary handoffs or fail to make necessary handoffs. Both of which lead to poorer device and/or system performance. Therefore, the device must be tested to ensure that it can make accurate signal strength determinations in the face of signals from a plurality of sectors even when fading is present.
Accordingly, in order to test a wireless communication device in the factory, fading and handoff conditions must be simulated. Unfortunately, realistic RF fading is very difficult to artificially simulate due to the number of different factors that effect fading and the unpredictable nature of these factors.
Presently a conventional method to simulate RF fading in the lab is static and empirical, i.e., it involves presetting parameters for mean path loss, fast fading, slow fading, and Doppler shift for a channel simulator, or fader, that are based on empirical results. The preset parameters in most cases are time independent. For example, in the CDMA 2000 1× standard document TIA/EIA 98D, Rayleigh fading scenarios are designed to be imposed on each of a maximum of 3 paths per channel in the lab. The model parameters for Rayleigh fading are predefined as 3, 8, 14, 30, 100 km/s, depending on the configuration (see Section 3.4.2, 3.4.7, 3.4.8, 3.4.9, 3.4.10 of the above specification). In the GSM Recommendation V3.5.0, on the other hand, 6 paths in one or two RF channels are faded by Rayleigh or Rician models, which also are superimposed on a log-normal fading model to mimic a rural, hilly, or urban terrain.
In both the CDMA 2000 1× and GSM examples, the predefined fast fading parameters wouldn't be changed during an entire test period for a given configuration. Real world fading scenarios, however, are neither static, nor in complete accordance with Rayleigh or Rician fading models. As measured data from the field has demonstrated, LOS and non-LOS signal areas randomly appear over time or distance as a receiver moves through a wireless communication environment. This means that a static, single fast fading math model does not represent realistic fading scenarios. Further, field data has indicated that the received baseline power dramatically changes with time. Thus, a high error margin must be added into conventional shadow fading math models, which is not considered in existing specifications such as the CDMA 2000 1X specification.
Two approaches have been considered to simulate realistic fading propagation in the lab. The first approach is based on the time-varying impulse response of a radio channel as measured by various radio channel sounding systems. A typical example is Electrobit Group's product PROPSound™, which employs a spread spectrum (SS) sounding method for the delay domain measurement. The measured data is further treated by some mathematical models. The treated data is presented in terms of propagation path delay, complex amplitude, Doppler shift, and azimuth/elevation angle, which is recreated by a channel simulator. While this approach can provide an instant picture of the channel properties between a transmitter and receiver, for example, its application is widely limited.
The limitations include the fact that a fundamental assumption in radio channel sounding is to consider the radio channel between a transmitter and a receiver as a time-varying filter. Thus, the radio channel's properties are fully disclosed by the filter's pulse response in the delay domain. The sounding measurement must use a RF transmitter and a RF receiver to carry out delay domain testing. Unfortunately, for a well established wireless communications system consisting of multiple base stations comprising multiple sectors and that has been in daily operation, it is typically impossible to allow any sounding measurements to be carried out in the field. As a result, today's sounding techniques are most applicable for exploring new frequency bands or new wireless application areas that are not in service.
Another limitation is the changing nature of wireless communication systems. Field measurements have demonstrated that due to the fast growth of wireless services, wireless network planners are forced to swiftly modify and add new base stations/sectors to existing wireless systems. Thus, measurements of radio channel properties, obtained through conventional sounding techniques, are only accurate for a short period of time before the wireless system is modified.
Another limitation is the fundamental challenge to any sounding base technique that is posed by IS-95 type systems. As mentioned above, fast fading and fading power spectrum properties are caused by multipath interference. The multipath signals in an IS-95 compliant system, however, actually are originated not from one source, but from many sources. This is because multiple base stations and their sectors can share the same carrier frequency in the same geographic area. Thus, multipath fading properties result from many multiple paths, and each channel's multipath must be described by a series of time-varying variables that depend on that channel's multipath conditions and the receiver's movement. In order to simulate a realistic fading environment, the sounding technique must be capable of synchronously measuring the channel properties for each channel and each base station and their sectors. The system must also be able to synthesize each channel's fading properties as seen by the receiver. These challenges are very expensive for existing channel sounding system to overcome, if it is even possible to do so.
The second approach to realistic fading simulation can be described as reverse engineering based on the First Principle of fading theory. Unfortunately, this approach also suffers from some fundamental limitations. First, for any reverse engineering process, the first step must be to abstract all fading information from the field propagation data (Abstraction Stage). The second step includes the recreation of the fading propagation based on the abstracted information to a controlled environment (Recreation Stage).
For the Abstraction Stage, some approaches separate fading into different signal components based on tiered theoretical fading models, and then find the model's parameters to describe these components. For example, when one base station is operated in a narrow band system, one approach takes RF signal versus time information 208 gathered in the field and separates it into three main components as illustrated in the graph of FIG. 2A. These components include the mean path loss 202, which is due to dispersion and is inversely, and exponentially proportional to the distance traveled; fast fading 204, which is due in part to the multipath effects described above; and slow fading 206. Also, in the frequency domain, the interference between multipaths coupled with the Doppler effect, caused by the device's relative movement to the base station, results in PSD fading 209 illustrated in FIG. 2B. As can be seen, PSD fading 209 is increased from its carry frequency (fc) location to a maximum at (fc±fm), where (fm) is the Doppler frequency.
It can also be seen that, the fast fading component 204 superimposes a large variation, e.g., maximum +10˜−30 dB, onto the slow fading variations 206, which can vary by 6˜10 dB around the mean path loss 202. In the frequency domain, the maximum PSD shift is dependent on the Doppler frequency (fm) in both Rayleigh and Rician fading cases. Further, the existence of a LOS signal in Rician fading also introduces a peak signal 210 at fD, where (fc−fm)<fD<(fc+fm).
Next, some parameters associated with each component must be abstracted out of the data. For example, the parameter d and n in the term l/dn, where d is the distance traveled at a given time t and n is 2 for free space but typically between 3 to 5 for wireless communication systems, must be found for the mean path loss 202. A series of parameters based on the contour and transmitter antenna sizes as well as other parameters associated with slow fading component 206 must also be abstracted. The velocity of the receiver relative to the base station, and whether a LOS signal is present must also be found for fast fading components 204 and 209.
In the Recreation Stage, once the parameters are defined, then they can be used to form a series of computer codes to feed to a channel simulator, or fader. The function of the fader is to modulate a test RF signal from a base station or a base station emulator. Thus, one test signal is faded in the time and frequency domains. This is illustrated in FIG. 3. Fader 310 is controlled by a computer 312, which provides Fader 310 with codes developed from the parameters associated with components 202, 204, 206, 209 and 210. A test signal 300 is shown in both the time (t) and frequency (f) domains, is modulated by fader 310 resulting in a signal 308 that comprises the components 302, 304, 306, 309, and 310. Signal 308 can also be combined with other modulated test signals to recreate an artificial fading environment for testing a wireless communication device.
In realty, however, it is very difficult to accurately create a realistic RF environment using the reverse engineering approach, described in relation to FIGS. 2 and 3. The difficulty results from several inherent limitations. The first and also the most difficult limitation to overcome is how to find the right time boundaries for recorded RF signals such that the meaningful parameters of fading theory can be assigned to each component within the boundaries. It has been found that the time boundaries for each fading component are different. In a slow fading situation, for example, all slow fading statistical models are highly dependent on the contours of the surrounding terrain. Thus, in order to abstract the parameters for a slow fading model, the time boundaries in the data file must first be determined. Then the unique contour characteristics must be found.
Suppose a slow fading time boundary spans from (t1) to (t2) and includes meaningful parameters (a1, a2, . . . ), and from (t3) to (t4) including parameters (b1, b2 . . . ), while for the same time period (t1) to (t4) the device experiences a couple of Rician fading peaks, each with a LOS signal. The overlapping boundary phenomena make any meaningful separation of the fading components impossible.
Another limitation is the very high error margin, as high to 6˜8 dB, that exists between the measured data and mathematical mean path loss models in wireless communication systems. Thus, during the Abstraction Stage, one set of accurately abstracted mean path loss parameters within a pair of particular time boundaries is most likely useless for all other time boundaries, not to mention for other log files obtained along the same path but at a different time. This makes any attempt to separate the RF baseline from the fading signals very difficult.
Still another limitation is that in Spread Spectrum (SS) wireless system, such as IS-95 compliant systems the same carry frequency can be reused in all neighboring cells. This means that the field recorded data is not only affected by the RF signals originated from one sector, but rather it is effected by the signals originated from two or more sectors. The number of sectors that actually contribute is case dependent and a function of the given locations. Thus, for a given time (t), the factors that contribute to the recorded data include the location of test device in the field, the channel conditions between the test device and surrounding sectors, the RF transmission conditions from each of the sectors, the spectrum reuse arrangement used by the service provider, etc. Without partitioning to separate each sector's contribution to the received RF signals, any attempt to abstract the parameters to generate fading models that describe each path's propagation is useless.
Thus, one can conclude that the reverse engineering process described above is highly limited in its effectiveness for reproducing a realistic fading environment. Thus, the conventional methods of simulating a fading environment for testing in the factory are therefore insufficient to ensure optimum operation of wireless communication devices in the field. This leads to inefficient device/system performance, especially in heavy handoff areas where fading is present.